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import pandas as pd
import folium
from folium.features import GeoJsonTooltip
import requests

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# Path to your CSV file
csv_file_path = '../data/data.csv'
variable_options = [
    'Total bridges',
    'Bridges, poor',
    'Bridges, fair',
    'Bridges, good',
    'Bridge area (square meters)',
    'Bridge area, poor (square meters)',
    'Bridge area, fair (square meters)',
    'Bridge area, good (square meters)'
]

df = pd.read_csv(csv_file_path)
# df.columns

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# Mapping for renaming and scaling
name_scale_mapping = {
    'Total bridges': {
        'new_name': 'Total Bridges (100)',
        'scale': 100
    },
    'Bridges, poor': {
        'new_name': 'Total Poor Bridges (100)',
        'scale': 100
    },
    'Bridges, fair': {
        'new_name': 'Total Fair Bridges (100)',
        'scale': 100
    },
    'Bridges, good': {
        'new_name': 'Total Good Bridges (100)',
        'scale': 100
    },
    'Bridge area (square meters)': {
        'new_name': 'Total Bridge Area (10k m²)',
        'scale': 10000
    },
    'Bridge area, poor (square meters)': {
        'new_name': 'Total Poor Bridge Area (10k m²)',
        'scale': 100000
    },
    'Bridge area, fair (square meters)': {
        'new_name': 'Total Fair Bridge Area (10k m²)',
        'scale': 100000
    },
    'Bridge area, good (square meters)': {
        'new_name': 'Total Good Bridge Area (10k m²)',
        'scale': 100000
    },
}

# Apply renaming and scaling based on the mapping
for original_name, props in name_scale_mapping.items():
    updated_rows = df['Variable'] == original_name  # Capture the rows to update
    df.loc[updated_rows, 'Variable'] = props['new_name']
    df.loc[updated_rows, 'Value'] /= props['scale']  # Apply scaling only to the updated rows

variable_options = [props['new_name'] for props in name_scale_mapping.values()]

# Define color scheme for each category
color_scheme = {
    'Total': 'Blues',
    'Poor': 'Reds',
    'Fair': 'Oranges',
    'Good': 'Greens'
}

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folium_counties_url = "https://raw.githubusercontent.com/python-visualization/folium/main/tests/us-counties.json"
us_counties = requests.get(folium_counties_url).json()

# Define state FIPS codes to drop (Hawaii, Alaska, DC)
fips_to_drop = ['02', '15', '11']  # FIPS codes for AK, HI, DC respectively

# Filter out counties based on their state FIPS code
us_counties['features'] = [
    feature for feature in us_counties['features']
    if feature['id'].zfill(5)[:2] not in fips_to_drop  # Ensure IDs are 5 digits for uniform comparison
]

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# Create a folium Map object, centered on the US, *without* a tile layer yet
m = folium.Map(
    [43, -100],
    zoom_start=4,
    tiles=None
)
# # Add the TileLayer to m *separately*, with control=False so that users
# # are not able remove the layer by unchecking a checkbox
folium.TileLayer('CartoDB positron',name="Light Map",control=False).add_to(m)

<folium.raster_layers.TileLayer at 0x1dc273d3940>

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# Loop through each variable option to create separate choropleth layers
for variable in variable_options:
    subset_df = df[df['Variable'] == variable]
    legend_label = variable.replace('_', ' ').title()
    if 'Poor' in variable:
        color = color_scheme['Poor']
    elif 'Fair' in variable:
        color = color_scheme['Fair']
    elif 'Good' in variable:
        color = color_scheme['Good']
    else:  # Default to 'Total' for any other cases, typically 'Total'
        color = color_scheme['Total']

    choro = folium.Choropleth(
        geo_data=us_counties,
        name=variable,
        data=subset_df,
        columns=['GEOID', 'Value'],  # Changed from ['State', 'Value']
        key_on='feature.id',  # Ensure this matches your county GeoJSON
        fill_color=color,
        fill_opacity=0.7,
        line_opacity=0.2,
        legend_name=legend_label,
        highlight=True,
        show=(variable == 'Total Bridges (100)'),
        overlay=False
    ).add_to(m)

    # Add tooltips to each layer
    tooltip = GeoJsonTooltip(
        fields=['name'],
        aliases=['County:'],
        localize=True,
        sticky=False,
        labels=True,
        style="""
            background-color: #F0EFEF;
            border: 2px solid black;
            border-radius: 3px;
            box-shadow: 3px;
        """,
        max_width=800,
    )
    choro.geojson.add_child(tooltip)

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folium.LayerControl(collapsed=False).add_to(m)

<folium.map.LayerControl at 0x1dc2bce0790>

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m

Make this Notebook Trusted to load map: File -> Trust Notebook

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m.save('.fullscreen_explore_map.html')